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Notes On Randomized Algorithms
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Book Synopsis Notes on Randomized Algorithms by : James Aspnes
Download or read book Notes on Randomized Algorithms written by James Aspnes and published by . This book was released on 2014-12-05 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Notes on Randomized AlgorithmsBy James Aspnes
Book Synopsis Randomized Algorithms by : Rajeev Motwani
Download or read book Randomized Algorithms written by Rajeev Motwani and published by Cambridge University Press. This book was released on 1995-08-25 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many applications a randomized algorithm is either the simplest algorithm available, or the fastest, or both. This tutorial presents the basic concepts in the design and analysis of randomized algorithms. The first part of the book presents tools from probability theory and probabilistic analysis that are recurrent in algorithmic applications. Algorithmic examples are given to illustrate the use of each tool in a concrete setting. In the second part of the book, each of the seven chapters focuses on one important area of application of randomized algorithms: data structures; geometric algorithms; graph algorithms; number theory; enumeration; parallel algorithms; and on-line algorithms. A comprehensive and representative selection of the algorithms in these areas is also given. This book should prove invaluable as a reference for researchers and professional programmers, as well as for students.
Book Synopsis Probability and Computing by : Michael Mitzenmacher
Download or read book Probability and Computing written by Michael Mitzenmacher and published by Cambridge University Press. This book was released on 2005-01-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.
Book Synopsis Concentration of Measure for the Analysis of Randomized Algorithms by : Devdatt P. Dubhashi
Download or read book Concentration of Measure for the Analysis of Randomized Algorithms written by Devdatt P. Dubhashi and published by Cambridge University Press. This book was released on 2009-06-15 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff–Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff–Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians.
Book Synopsis Algorithms for Random Generation and Counting: A Markov Chain Approach by : A. Sinclair
Download or read book Algorithms for Random Generation and Counting: A Markov Chain Approach written by A. Sinclair and published by Springer Science & Business Media. This book was released on 1993-02 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is a slightly revised version of my PhD thesis [86], com pleted in the Department of Computer Science at the University of Edin burgh in June 1988, with an additional chapter summarising more recent developments. Some of the material has appeared in the form of papers [50,88]. The underlying theme of the monograph is the study of two classical problems: counting the elements of a finite set of combinatorial structures, and generating them uniformly at random. In their exact form, these prob lems appear to be intractable for many important structures, so interest has focused on finding efficient randomised algorithms that solve them ap proxim~ly, with a small probability of error. For most natural structures the two problems are intimately connected at this level of approximation, so it is natural to study them together. At the heart of the monograph is a single algorithmic paradigm: sim ulate a Markov chain whose states are combinatorial structures and which converges to a known probability distribution over them. This technique has applications not only in combinatorial counting and generation, but also in several other areas such as statistical physics and combinatorial optimi sation. The efficiency of the technique in any application depends crucially on the rate of convergence of the Markov chain.
Book Synopsis Probabilistic Methods for Algorithmic Discrete Mathematics by : Michel Habib
Download or read book Probabilistic Methods for Algorithmic Discrete Mathematics written by Michel Habib and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leave nothing to chance. This cliche embodies the common belief that ran domness has no place in carefully planned methodologies, every step should be spelled out, each i dotted and each t crossed. In discrete mathematics at least, nothing could be further from the truth. Introducing random choices into algorithms can improve their performance. The application of proba bilistic tools has led to the resolution of combinatorial problems which had resisted attack for decades. The chapters in this volume explore and celebrate this fact. Our intention was to bring together, for the first time, accessible discus sions of the disparate ways in which probabilistic ideas are enriching discrete mathematics. These discussions are aimed at mathematicians with a good combinatorial background but require only a passing acquaintance with the basic definitions in probability (e.g. expected value, conditional probability). A reader who already has a firm grasp on the area will be interested in the original research, novel syntheses, and discussions of ongoing developments scattered throughout the book. Some of the most convincing demonstrations of the power of these tech niques are randomized algorithms for estimating quantities which are hard to compute exactly. One example is the randomized algorithm of Dyer, Frieze and Kannan for estimating the volume of a polyhedron. To illustrate these techniques, we consider a simple related problem. Suppose S is some region of the unit square defined by a system of polynomial inequalities: Pi (x. y) ~ o.
Book Synopsis New Trends in Discrete and Computational Geometry by : Janos Pach
Download or read book New Trends in Discrete and Computational Geometry written by Janos Pach and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete and computational geometry are two fields which in recent years have benefitted from the interaction between mathematics and computer science. The results are applicable in areas such as motion planning, robotics, scene analysis, and computer aided design. The book consists of twelve chapters summarizing the most recent results and methods in discrete and computational geometry. All authors are well-known experts in these fields. They give concise and self-contained surveys of the most efficient combinatorical, probabilistic and topological methods that can be used to design effective geometric algorithms for the applications mentioned above. Most of the methods and results discussed in the book have not appeared in any previously published monograph. In particular, this book contains the first systematic treatment of epsilon-nets, geometric tranversal theory, partitions of Euclidean spaces and a general method for the analysis of randomized geometric algorithms. Apart from mathematicians working in discrete and computational geometry this book will also be of great use to computer scientists and engineers, who would like to learn about the most recent results.
Book Synopsis Twenty Lectures on Algorithmic Game Theory by : Tim Roughgarden
Download or read book Twenty Lectures on Algorithmic Game Theory written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2016-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Download or read book Algorithms written by Jeff Erickson and published by . This book was released on 2019-06-13 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are the lifeblood of computer science. They are the machines that proofs build and the music that programs play. Their history is as old as mathematics itself. This textbook is a wide-ranging, idiosyncratic treatise on the design and analysis of algorithms, covering several fundamental techniques, with an emphasis on intuition and the problem-solving process. The book includes important classical examples, hundreds of battle-tested exercises, far too many historical digressions, and exaclty four typos. Jeff Erickson is a computer science professor at the University of Illinois, Urbana-Champaign; this book is based on algorithms classes he has taught there since 1998.
Download or read book Algorithms written by M. H. Alsuwaiyel and published by World Scientific. This book was released on 1999 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) solution of the formulated problem. One can solve a problem on its own using ad hoc techniques or follow those techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions and the context appropriate for each of them. This book advocates the study of algorithm design techniques by presenting most of the useful algorithm design techniques and illustrating them through numerous examples.
Book Synopsis Algorithms: Design Techniques And Analysis (Second Edition) by : M H Alsuwaiyel
Download or read book Algorithms: Design Techniques And Analysis (Second Edition) written by M H Alsuwaiyel and published by World Scientific. This book was released on 2021-11-08 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This required the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.This book presents a design thinking approach to problem solving in computing — by first using algorithmic analysis to study the specifications of the problem, before mapping the problem on to data structures, then on to the situatable algorithms. Each technique or strategy is covered in its own chapter supported by numerous examples of problems and their algorithms. The new edition includes a comprehensive chapter on parallel algorithms, and many enhancements.
Book Synopsis Bandit Algorithms by : Tor Lattimore
Download or read book Bandit Algorithms written by Tor Lattimore and published by Cambridge University Press. This book was released on 2020-07-16 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Book Synopsis Pseudorandomness by : Salil P. Vadhan
Download or read book Pseudorandomness written by Salil P. Vadhan and published by Foundations and Trends(r) in T. This book was released on 2012 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of pseudorandomness, the theory of efficiently generating objects that look random despite being constructed using little or no randomness. This theory has significance for areas in computer science and mathematics, including computational complexity, algorithms, cryptography, combinatorics, communications, and additive number theory.
Book Synopsis Algorithms to Live By by : Brian Christian
Download or read book Algorithms to Live By written by Brian Christian and published by Macmillan. This book was released on 2016-04-19 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Algorithms to Live By' looks at the simple, precise algorithms that computers use to solve the complex 'human' problems that we face, and discovers what they can tell us about the nature and origin of the mind.
Download or read book Algorithms written by Sanjoy Dasgupta and published by McGraw-Hill Higher Education. This book was released on 2006 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text DasGupta also offers a Solutions Manual which is available on the Online Learning Center."Algorithms is an outstanding undergraduate text equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel it is a joy to read." Tim Roughgarden Stanford University
Book Synopsis Randomized Algorithms for Analysis and Control of Uncertain Systems by : Roberto Tempo
Download or read book Randomized Algorithms for Analysis and Control of Uncertain Systems written by Roberto Tempo and published by Springer Science & Business Media. This book was released on 2012-10-21 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms; · comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples; · applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems. Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties. The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years. M. Vidyasagar
Book Synopsis Randomized Algorithms by : Rajeev Motwani
Download or read book Randomized Algorithms written by Rajeev Motwani and published by Cambridge University Press. This book was released on 1995-08-25 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents basic tools from probability theory used in algorithmic applications, with concrete examples.